Cross-Sectional Study of the Relationship Between Medial Plantar Nerve Conduction Studies and Severity of Diabetic Neuropathy
Bibliographic record
Abstract
Objective: Diabetic peripheral neuropathy (DPN), a complication of diabetes, is detected only in later stages. Medial plantar nerve (MPL) can identify earlier stages of neuropathy. We evaluated the correlation of MPL sensory nerve action potentials (SNAPs) and severity of DPN measured using the Toronto Clinical Neuropathy Score (TCNS). Methods: In this hospital-based, cross-sectional study, we recruited diabetic subjects referred for suspected DPN. Neuropathy was graded with TCNS. Sural nerve conduction studies were performed using standard techniques. MPL studies were conducted using the modified Ponsford technique. All evaluations were performed on Nihon Kohden (model MEB 9200K). Averaged MPL SNAP was correlated with TCNS using Pearson’s correlation coefficient. To estimate a correlation of 0.4 with 80% power ( P = 0.05), we needed 46 subjects. Linear regression was conducted to adjust for age, duration, and diabetic control. Receiver operating characteristic (ROC) curve analysis was performed to obtain the cutoff for MPL SNAP values using the Youden index. Results: Fifty-one subjects with a mean age of 53.5 years (8.7) and mean duration of diabetes of 10.2 years (7.2) were included. MPL SNAPs were recordable in 12 patients, and the mean amplitude was 5.15 (2.9) µV. There was correlation between MPL SNAP and TCNS ( r = -0.43, P = 0.02). No confounding was seen. Use of MPL SNAP resulted in diagnosis of DPN in an additional six (11.8%) patients. The ROC curve suggested that MPL SNAP cutoff of 1.05 µV had an accuracy of 67% in identifying neuropathy as defined by TCNS. Conclusions: MPL SNAP has a moderate correlation with clinical score and identifies more diabetic neuropathy than sural nerve.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".